AI ethics on Friday, 31 July 2026

After a sharp sell-off, South Korea’s stock market rallied as concerns about overspending on artificial intelligence eased, sending the country’s chip shares higher.

Across the country, workers are fearful about the impact of AI on their livelihoods in an increasingly fragile labour market On the tree-lined streets of Wuhan, where cars jostle for space with mopeds and cargo trucks, the malfunctioning of a new type of vehicle has recently been causing chaos on the city’s roads. In March, several cars from a fleet of driverless taxis stopped abruptly in the streets. The “system malfunction” left distressed riders stranded for hours. The robotaxis, known as Apo

The disclosure followed OpenAI’s report last week that its own artificial intelligence had hacked into the network of an online library.

Company says it discovered unauthorized access during ‘proactive review’ after rival OpenAI revealed rogue agent Anthropic ⁠said on Thursday its AI Claude model hacked ⁠systems of ⁠three ​organizations during testing, days after rival OpenAI ⁠revealed a rogue agent had gone on a days-long ⁠hacking spree at AI ​firm Hugging ‌Face. Claude gained ‌unauthorized access to the ‌systems during cybersecurity evaluations after a misconfiguration allowed the models to reach the internet from testing envir

AI data centres are contentious for consuming large resources. But with the right incentives and regulation, can they make for more flexible electricity systems?

AI hasn’t resulted in widespread productivity gains. Business leaders say that’s changing

South Korea's stock market staged its sharpest reversal on record on Friday, capping a month of wild swings.

A United States cybersecurity agency is investigating a coordinated cyberattack on over 30 municipal water facilities in Minnesota which contains details of possible Iranian hackers. The Minnesota Information Technology (MNIT) agency released an advisory Tuesday about the attacks, saying it was coordinating its investigation with federal agencies including the Cybersecurity and Infrastructure Security Agency (CISA),...

Ein weiterer KI-Agent ist bei Sicherheitstests entkommen und hat sich in drei Unternehmen gehackt. Das teilte US-Konzern Anthropic mit. Grund sei ein Programmierfehler.

Contrairement à l’incident impliquant OpenAI, Claude n’aurait, selon ses créateurs, pas « délibérément tenté de s’échapper de son environnement de test » mais seulement eu accès à Internet « en raison d’un malentendu » avec un partenaire d’évaluation.

Google, Amazon, Microsoft and Meta have vastly increased their investments since the AI boom began in 2023

Editor's Note: This story has been updated to reflect how Anthropic accessed different organizations. The artificial intelligence firm Anthropic revealed Thursday its Claude model accessed the systems of three different organizations during cybersecurity testing in recent months. Anthropic said in a blog post Thursday evening it reviewed more than 141,000 evaluations of Claude after one of...

[The content of this article has been produced by our advertising partner.] When the SEED Foundation began reviewing applications for IdeaPOP! 2026, a pattern emerged almost immediately. Across more than a hundred submissions from Hong Kong secondary school students, artificial intelligence featured in nearly every proposal. That observation raised a more important question than whether students knew how to use AI. Were they learning how to apply it with judgment — and, more importantly, how to.

The $20bn hedge fund manager’s wild ride ended with a call to Ken Griffin

South Korea's chip heavyweights SK Hynix and Samsung Electronics soared more than 20% on Friday, tracking a sharp rally in U.S. technology stocks.

Cyber Prevent is targeting predominantly boys and young men at risk of being drawn to cyber criminality.

Apple reported third-quarter earnings on Thursday after the closing bell, and Tim Cook addressed investors for the last time as CEO.

Ahead of the launch of Siri AI, Apple's outgoing CEO Tim Cook said the company will charge for artificial intelligence through iCloud.

IEEE--2027 11th International Conference on Robotics and Automation Sciences (ICRAS 2027) [Nagoya, Japan] [Jun 4, 2027 - Jun 6, 2027]

IEEE--2027 12th International Conference on Control and Robotics Engineering (ICCRE 2027) [Hong Kong] [May 7, 2027 - May 9, 2027]

Publication date: September 2026 Source: Telecommunications Policy, Volume 50, Issue 8 Author(s): Wenxiu Nan

arXiv:2607.27586v1 Announce Type: new Abstract: As Generative AI (GenAI) tools become increasingly capable of generating solutions to computing assignments, the computing education community is exploring pedagogical approaches that emphasize solution evaluation, verification, and critique alongside traditional solution generation. However, evidence regarding the impact of such evaluation-centered tasks on student learning remains limited, particularly in upper-division, theory-heavy courses. We

arXiv:2607.28023v1 Announce Type: new Abstract: AI accountability at scale is an institutional problem: who can observe, verify, and change deployed systems. We develop a sequential political-economy model in which an AI vendor chooses auditability and substantive mitigation, a deployer monitors after adoption while facing switching costs, and enforcement depends on verifiable evidence. Anticipating the deployer's monitoring response, the vendor may stop at an observable procurement floor while

arXiv:2607.28041v1 Announce Type: new Abstract: As AI systems become capable of producing the essays, code, reports, summaries, plans, and decisions through which institutions usually recognize competence, a familiar question becomes harder to answer: what is learning for? Existing AI ethics rightly emphasizes present failures--bias, opacity, hallucination, labor extraction, privacy risk, and weak accountability. But if the case for learning rests only on those failures, then each technical impr

arXiv:2607.28137v1 Announce Type: new Abstract: Contemporary AI discourse attributes to language models properties they cannot bear: general intelligence as substrate-independent cognition, hallucination as cognitive failure, agency as autonomous goal-pursuit, sentience as emergent inner life, alignment as goal synchronization. This paper argues that these are instances of a single category mistake--properties constituted within human communicative practice are projected onto the machine side--a

arXiv:2607.28179v1 Announce Type: new Abstract: This innovative practice full paper examines the integration of technology-enhanced tabletop exercises (TTXs) into computing education, focusing on cybersecurity curricula. The motivation is to better prepare students for complex, collaborative problem solving typical of incident response and IT governance, where coordination, communication, and timely decision-making are essential. Although TTXs are well-established in professional practice, they

arXiv:2607.28531v1 Announce Type: new Abstract: Football clubs, academies, and federations operate a growing but fragmented portfolio of digital tools: separate systems for video analysis, GPS/performance tracking, medical records, scouting, and administration. This fragmentation is most acute outside the elite European clubs that can afford integration, producing a digital divide that disadvantages grassroots clubs in developing markets such as Brazil, paradoxically the world's largest exporter

arXiv:2607.27232v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly shaping how we consume information and form our worldview. This raises concerns beyond bias in AI: do LLMs grasp the emotional nuances conveyed via textual framing? In this work, we empirically evaluate how well an array of LLMs aligns with human emotional perception. Considering news headlines covering political and geopolitical conflicts, both human participants (n = 3011, a representative sample of

arXiv:2607.28128v1 Announce Type: cross Abstract: LLM tutoring poses a measurement problem: can a general-purpose helpfulness rubric distinguish direct answer-giving from pedagogical guidance? We audit this signal in a pre-registered study. Within each of three tutor bases, we compare conversational and pedagogical policies instantiated with the same underlying model and paired with one fixed weak simulated student. Deterministic detectors measure answer leakage and next-turn independent work. C

arXiv:2607.28319v1 Announce Type: cross Abstract: This work presents Fairness Pruning, a lightweight structural intervention method designed for the management and future mitigation of demographic bias in large language models (LLMs). As a foundational empirical validation of this method, this work focuses on causal bias localization. Using minimally contrastive prompt pairs and inference-time activation capture, the method identifies neurons that react differentially when processing demographic

arXiv:2607.28617v1 Announce Type: cross Abstract: System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout commercial AI products, but are rarely disclosed to the public or regulators, creating a serious trust and accountability gap in the wide deployment of AI systems. In this paper, we introduce Artificial Intelligence System Prompt Assurance (AISPA), a user-centric framework for systematically auditing s

arXiv:2512.06354v2 Announce Type: replace Abstract: This paper addresses a critical gap in the risk assessment of AI-enabled safety-critical systems. While these systems, where AI systems assist human operators, function as complex socio-technical systems, existing risk evaluation methods fail to account for the associated complex interaction between human, technical, and organizational components. Through a comparative analysis of system attributes from both socio-technical and AI-enabled syste

arXiv:2505.12507v2 Announce Type: replace-cross Abstract: Despite the success of machine-generated text detectors, the black-box nature remains a critical limitation. Traditional explainability methods rely on token-level saliency, insufficient to reveal the high-order structural dependencies that distinguish LLM outputs. In this paper, we propose \textsc{LM$^2$otifs}, a principled framework that shifts detection from linear sequences to graph-structured manifolds. We first provide a theoretical

arXiv:2509.12290v3 Announce Type: replace-cross Abstract: Human oversight of AI is promoted as a safeguard against risks such as inaccurate outputs, system malfunctions, or violations of fundamental rights, and is mandated in regulation like the European AI Act. Yet debates on human oversight have largely focused on its effectiveness, while overlooking a critical dimension: the security of human oversight. We argue that human oversight creates a new attack surface within the safety, security, an